S6E2: Prasanna Balaprakash: Predicting Earth Systems and Harnessing Swarms for Computing
Science in Parallel
In the second episode in our series on foundation models for science, we discuss Oak Ridge National Laboratory's work and hear about lessons learned from the recent 1000 Scientists AI Jam, a recent event that brought together researchers from several Department of Energy national laboratories, OpenAI and Anthropic. My guest is Prasanna Balaprakash, ORNL's director of AI programs. We talk about how foundation models could help with climate forecasts and his team's 2024 Gordon Bell finalist research and futuristic work that applies principles of swarm intelligence for managing distributed...
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S6E1 - Ian Foster: Exploring and Evaluating Foundation Models
Science in Parallel
Large language models aren't just powering chatbots like ChatGPT. This type of computational model is an example of a particular flavor of artificial intelligence known as foundation models, which are trained on vast amounts of data to make inferences in new areas. Although text is one rich data source, science offers many more from biology, chemistry, physics and more. Such models open up a tantalizing new set of research questions. How effective are foundation models for science? How could they be improved? Could they help researchers work on challenging questions? And what might they mean...
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S5E7 - Computational Scientists Discuss 2024 Nobel Prizes
Science in Parallel
Wrapping up our discussion of the 2024 Nobel Prizes in Physics and Chemistry, computer scientist Mansi Sakarvadia and computational structural biologist Josh Vermaas talk about the recent prizes and what they mean for science. You'll hear about how the prizes both break down research barriers and introduce concerns about misinformation and public trust. The research honored with the chemistry prize has already changed how researchers study questions that involve understanding proteins' structures. For more on the 2024 Nobel Prizes, check out . You'll meet: is a Ph.D. student in the and...
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S5E6 - Anil Ananthaswamy: AI's Nobel Moment
Science in Parallel
2024 was artificial intelligence’s Nobel Prize year with the physics and chemistry prizes recognizing the underpinnings and application of these algorithms. Science journalist and author Anil Ananthaswamy spent years writing a popular book, Why Machines Learn: The Elegant Math Behind Modern AI, that explores the equations and historical context for this technology. In this conversation, Anil and host Sarah Webb explore that math and history, the significance of these Nobel Prizes for both AI and science, and the challenges that come with this powerful and fast-moving technology. You’ll...
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S5E5 - Sadie Bartholomew: Patterns in Computing and Art
Science in Parallel
The annual convenes November 17-22 in Atlanta with the theme of HPC creates, and Science in Parallel previews a special display at the meeting: . Host Sarah Webb interviews Sadie Bartholomew of the United Kingdom's and the about her work as a research software engineer and her passion for creative coding. She submitted several pieces of digital art that will be displayed at SC24. Sadie discussed the many patterns in her work—within weather and climate, in coding and in digital art. She makes her pieces using matplotlib, a visualization tool in Python. She talks about the synergy and...
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S5E4 - Paulina Rodriguez: Building Credibility and Authenticity
Science in Parallel
Early in her applied math journey, Paulina Rodriguez was a little skeptical of calculators and computers. But her desire to really understand what’s going on under the hood has ultimately led to satisfying research. During her Ph.D., she’s explored the credibility of computational models for medical device applications, making sure that researchers understand the accuracy, validity and uncertainty of simulated results. Paulina shares how she honed her problem-solving skills and creativity as she navigated her education. Her enthusiasm and determination are infectious, and she describes her...
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S5E3 - Paul Sutter the Spaceman: Adventures in Science and Outreach
Science in Parallel
Science communication often attracts people with diverse interests, who thrive in multiple roles. Paul Sutter is no exception: he’s an astrophysicist, host, author and more. He’s also a visiting professor at Barnard College, Columbia University. Paul’s roots are in computational science, and he shares how his many projects continue to build on that foundation. We also discuss his most recent book: Rescuing Science: Restoring Trust in an Age of Doubt, which critiques today’s scientific enterprise and and offers ideas for supporting a better future. You'll meet: is a theoretical...
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S5E2 - Rogelio Cardona-Rivera Plays Games for Science
Science in Parallel
Video games are everywhere, but the fundamental elements that generate human reactions such as suspense or surprise aren’t understood. Instead, game designers start from scratch each time they want to build a new experience for players. Rogelio Cardona-Rivera of the University of Utah wants to understand games and the fundamental elements that make people respond as they do—as a science of games. The research is important for more than just gaming—Rogelio is working on a variety of projects, including artificial intelligence research, technology for Indigenous storytelling and virtual...
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S5E1 - Lois Curfman McInnes: Building Software Sustainability and Broadening Workforce Participation
Science in Parallel
The field of high-performance computing (HPC) currently faces dual challenges: important technical problems that require a skilled workforce and the need to recruit more computational researchers. This conversation with Lois Curfman McInnes of Argonne National Laboratory examines both the complexity in building scientific software and the work needed to build the HPC workforce of the future. You'll meet: is a senior computational scientist in the mathematics and computer science division at . She served as deputy director for the software technology focus are of the U.S. Department of...
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S4E4 - Anubhav Jain: Hacking Materials
Science in Parallel
Artificial intelligence is reshaping research to discover new materials for a range of important applications. In this episode, meet of Lawrence Berkeley National Laboratory, a researcher who has been at the forefront of this transition. He uses machine learning and other computational tools as a materials scientist to discover compounds that could store and convert energy and solve other societal problems. Anubhav’s current research path started in graduate school at MIT, where he was supported by a . We discuss how computational tools including AI have moved from a novel idea to a central...
info_outlineSeason 4 of Science in Parallel centers around creativity and computing, starting with an interview about climate modeling.
At this nexus of physics, earth science, mathematics and computing, researchers are also racing against the clock to accurately predict how global climate is shifting before the changes happen. Pulling all the scientific pieces together and communicating those results so that others can use them are significant creative challenges—ones that both Tapio Schneider and Emily de Jong of California Institute of Technology have embraced.
In our conversation, Tapio and Emily describe how both the science and societal impact of climate modeling motivate them, how outdoor activities and music shape their perspectives, and how they view creativity both inside and outside the lab. Later in the episode, Tapio shares his experience as a science advisor to the ClimateMusic Project—an artists’ collaboration that’s producing music and video pieces that explore climate change and solutions to the climate crisis.
You’ll meet:
Tapio Schneider is a professor of environmental science and engineering at Caltech. He’s a member of the Climate Modeling Alliance (CLiMA) a team of scientists, engineers and applied mathematicians from Caltech, MIT and NASA’s Jet Propulsion Laboratory working on a new earth system model that uses computatational and data-science tools to harness Earth observations and make more accurate climate predictions. He spoke about that research at the 2023 Annual Program Review of the Department of Energy Computational Science Graduate Fellowship (DOE CSGF) program in July.
Emily de Jong is a Ph.D. student in mechanical engineering at Caltech working in Tapio’s research group. She is a DOE CSGF recipient, who completed her undergraduate degree at Princeton University in 2019.